Performance complementarity of solvers available to tackle black-box
opt...
The L_∞ star discrepancy is a measure for the regularity of a finite
set...
Extending a recent suggestion to generate new instances for numerical
bl...
A key component of automated algorithm selection and configuration, whic...
Within the optimization community, the question of how to generate new
o...
Box-constraints limit the domain of decision variables and are common in...
The domain of an optimization problem is seen as one of its most importa...
Benchmarking plays a major role in the development and analysis of
optim...
Dynamic algorithm selection aims to exploit the complementarity of multi...
Submodular functions play a key role in the area of optimization as they...
Empirical data plays an important role in evolutionary computation resea...
Benchmarking is a key aspect of research into optimization algorithms, a...
Per-instance algorithm selection seeks to recommend, for a given problem...
The stochastic nature of iterative optimization heuristics leads to
inhe...
Selecting the most suitable algorithm and determining its hyperparameter...
Dynamic algorithm selection can be beneficial for solving numerical blac...
Landscape-aware algorithm selection approaches have so far mostly been
r...
We present IOHexperimenter, the experimentation module of the IOHprofile...
The ever-increasing need for random numbers is clear in many areas of
co...
Structural Bias (SB) is an important type of algorithmic deficiency with...
Many platforms for benchmarking optimization algorithms offer users the
...
Introducing new algorithmic ideas is a key part of the continuous improv...
In this short note, we describe our submission to the NeurIPS 2020 BBO
c...
We propose IOHanalyzer, a new software for analyzing the empirical
perfo...
One of the most challenging problems in evolutionary computation is to s...
When faced with a specific optimization problem, choosing which algorith...
In the field of evolutionary computation, one of the most challenging to...